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Dinamika Spatial. PPS Ilmu Geografi 2007. Ekonomi dan Bisnis selalu berubah. Apalagi yang akan datang ?. Hidup dari lingkungan. terkonvergnsi. Perdagangan regional baru. Berburu dan bertani. Tata dunia baru (metanasional). Export/ import. globalisasi.
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Dinamika Spatial PPS Ilmu Geografi 2007
Ekonomi dan Bisnis selalu berubah... Apalagi yang akan datang ? Hidup dari lingkungan terkonvergnsi Perdagangan regional baru Berburu dan bertani Tata dunia baru (metanasional) Export/ import globalisasi Berdagang / transaksi benda berharga (uang) Berdagang / barter Jaman imperialisme………….... Imperialisme gaya baru
Long Wave Cycles of Innovation Electricity Chemicals Internal-combustion engine Steam Rail Steel Water power Textiles Iron Petrochemicals Electronics Aviation Digital networks Software New Media Pace of innovation 1st Wave 2nd Wave 3rd Wave 4th Wave 5th Wave 1785 1845 1900 1950 1990 60 years 55 years 50 years 40 years 30 years
Kumulatif Sumbangan Moda Transportasi terhadap Peluang Ekonomis Revolusi Industrial Produksi Massal Globalisasi Telekomunikasi Udara Jalan darat Peluang Ekonomis Kereta Api Kapal Penyeberangan Kapal Laut Kuda 1750 1775 1800 1825 1850 1875 1900 1925 1950 1975 2000 2025 2050
Sectors of the Economy Tertiary Percent of Workforce Secondary Quaternary Primary Time
f ( I (t+1) ) Spatial dynamic systems f ( I (t) ) f ( I (t+2) ) f ( I (tn )) F F . . . Spatial dynamic systems simulates spatio-temporal processes in which the state of a location, on the Earth´s surface, changes over time, due to some physical phenomena.
Forecast tp + 10 calibration calibration Dynamic spatial models tp - 20 tp - 10 tp fonte: Almeida et al (2003)
Transition Rules Spatial dynamic system elements discrete continuous hybrid • Models Clue FuzzyL(Clue) Expander(Dinâmica) LocalMean (Riks) Dinâmica Riks
Spatial dynamic system elements • Space representation • Neighborhood uniform proprieties modelo celular • regular structure non stationary proximitry matrix
Look at change over time at several localities Look at change across space for several moments in time Space-time modeling: issues for current methods
Contoh Aplikasi berbasis Time-Space Convergence (spatial diffusion) t3 t3 t2 t2 t1 t1 Expansion Diffusion Relocation Diffusion Combination of Expansion and Relocation
Contoh Aplikasi: Over-bounded, under-bounded dan true-bounded Under-bounded Over-bounded True-bounded Batas funsional kota Batas administrasi
Epipaleo Early Neol Late Neol U. Paleo M. Paleo Space-time modeling: issues for current methods
High resolution diachronic record in one or a few sites unwarranted regional generalization across variable space High resolution spatial record for a few time periods past as a sequence of snapshots with change happening invisibly between (or stepwise change) Conceptualizing rich socioecological variation across space and complex dynamics through time desirable but difficult with current methods Space-time modeling: issues for current methods
Goals for study of long-term dynamics of human ecology High resolution models spatial chronological Link dynamically so that state of modeled ecosystem at any given time (t) is in part a function of ecosystem at prior time (t-1) and affects future state (t+1) State of modeled ecosystem at any given locale is in part a function of state in surrounding locales Test against archaeo-ecological record Future directions in space-time modeling
Future directions in space-time modeling: an example • Mediterranean Landscape Dynamics Project • Project locations at opposite ends of Mediterranean Basin • Encompasses wide range of ecological & social variation • Tracks initial spread of agriculture & replacement of foraging systems • Different trajectories to the appearance of social complexity and urbanism
3 interlinked modeling environments in GIS platform Potential landscape model Reference landscape chronosequence Agropastoral socioecology model Initial state Paleobotanical data Paleo- vegetation Veg. edaphic parameters Terrain modeling: multi-yr. steps Potential landscape model Modern DEM Climate model (temp&precip) Paleo- terrains (DEM’s) Reference landscape chronoseq. Vegetation modeling: multi-yr. steps Agent Modeling Agropastoral socioecology model Geological data Settlement & landuse modeling Vegetation modeling: multi-yr. steps Terrain modeling: multi-yr. steps Climate model (temp&precip) Prehistoric settlement & landuse Initial state & validation at various stages Archeological data Dynamic space-time modeling
Potential landscape model: surface processes and landcover Terrain modeling: multi-yr. steps Potential landscape model Climate model (temp&precip) Vegetation modeling: multi-yr. steps Dynamic space-time modeling
Reference landscape chronosequence: surface processes and landcover Paleobotanical data Paleo- vegetation Veg. edaphic parameters Modern DEM Paleo- terrains (DEM’s) Reference landscape chronoseq. Geological data Prehistoric settlement & landuse Archeological data Dynamic space-time modeling
Human landuse: agent simulation Agent Modeling Settlement & landuse impacts on terrain & vegetation Information Inputs Temp. extremes Precip. amt & dist Terrain characteristics Current vegetation Settlement Establish Shrink/grow Abandon Location Decision Algorithms Landuse Location/extent Cultivation (which crops) Pasture (which animals) Dynamic space-time modeling
Climate surface processes & landcover agent simulation Landscape socioecology Dynamic space-time modeling Polop Valley Landuse Intensity M. Paleolithicto Neolithic II Vegetation modeling: multi-yr. steps Agent Modeling Agropastoral socioecology model Settlement & landuse modeling Terrain modeling: multi-yr. steps Climate model (temp&precip)
Spatial Dynamic • Driven by : • Population • Economic activities • Technology • etc
Space – time Spatial changing dan changing overtime Spatial Thinking System Dynamic (1): Intro System Dynamic (2): Latihan Cases: Spatial Dynamic Materi Spatial Dynamic